Dear BioC users, Is there any way to analyze DNA ploidy histograms in FlowCore (FlowClust, FlowStats,...etc) package according to Dean-Jett-Fox, Watson or any other cell-cycle model? I have found the simmilar question here https://stat.ethz.ch/pipermail/bioconductor/2011-January/037449.html And the answer was to use clustering for identifying the G1,S,G2 population. I have tried to find some publication where this method was used for cell-cycle analysis, but I have found nothing. I understand that it is probably possible to fit such data using nls, or mixtools packages. But I wonder if there is any easiest way to do so? My own problem with e.g. Dean-Jett-Fox model than I don't clearly understand which kind of function they use for S-phase fit. And how then to calculate the percentage of the cells in different populations taking into account overlapping of the population in boundaries regions. So it would be probably hard for me to build the algorithm that could be used for analysis of my data . I would be very grateful to you for any help or suggestion. Kind regards, Dmytro -- output of sessionInfo(): R version 2.15.0 (2012-03-30) Platform: i686-pc-linux-gnu (32-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base -- Sent via the guest posting facility at bioconductor.org.